Dissecting Cell-Type Composition and Activity-Dependent Transcriptional State in Mammalian Brains by Massively Parallel Single-Nucleus RNA-Seq

Increased TMEM106B levels lead to lysosomal dysfunction which affects synaptic signaling and neuronal health

BACKGROUND

Genetic variation in Transmembrane protein 106B (TMEM106B) is known to influence the risk and presentation in several neurodegenerative diseases and modifies healthy aging. While evidence from human studies suggests that the risk allele is associated with higher levels of TMEM106B, the contribution of elevated levels of TMEM106B to neurodegeneration and aging has not been assessed and it remains unclear how TMEM106B modulates disease risk.

METHODS

To study the effect of increased TMEM106B levels, we generated Cre-inducible transgenic mice expressing human wild-type TMEM106B. We evaluated lysosomal and neuronal health using in vitro and in vivo assays including transmission electron microscopy, immunostainings, behavioral testing, electrophysiology, and bulk RNA sequencing.

RESULTS

We created the first transgenic mouse model that successfully overexpresses TMEM106B, with a 4- to 8-fold increase in TMEM106B protein levels in heterozygous (hTMEM106B(+)) and homozygous (hTMEM106B(++)) animals, respectively. We showed that the increase in TMEM106B protein levels induced lysosomal dysfunction and age-related downregulation of genes associated with neuronal plasticity, learning, and memory. Increased TMEM106B levels led to altered synaptic signaling in 12-month-old animals which further exhibited an anxiety-like phenotype. Finally, we observed mild neuronal loss in the hippocampus of 21-month-old animals.

CONCLUSION

Characterization of the first transgenic mouse model that overexpresses TMEM106B suggests that higher levels of TMEM106B negatively impacts brain health by modifying brain aging and impairing the resilience of the brain to the pathomechanisms of neurodegenerative disorders. This novel model will be a valuable tool to study the involvement and contribution of increased TMEM106B levels to aging and will be essential to study the many age-related diseases in which TMEM106B was genetically shown to be a disease- and risk-modifier.

A simplified preparation method for single-nucleus RNA-sequencing using long-term frozen brain tumor tissues

Single-cell RNA-sequencing has provided intriguing new insights into research areas such as developmental processes and tumor heterogeneity. Most approaches, however, rely on the availability of fresh surgical specimens, thereby dramatically reducing the ability to profile particularly rare tissue types. Here, we optimized a method to isolate intact nuclei from long-term frozen pediatric glioma tissues. We performed a technical comparison between different single-nucleus RNA-sequencing (snRNA-seq) systems and applied the established nucleus isolation method to analyze frozen primary glioma tissues. The results show that our fast, simple and low-cost nuclear isolation protocol provides intact nuclei, which can be used in both droplet- and plate-based single-cell sequencing platforms - allowing the identification of distinct tumor cell populations and infiltrating microglia. Additional optimization to include shorter RNA fragments in the 3' sequencing library improved gene detection and cell type annotation. Taken together, the method dramatically increases the potential of studying rare tumor entities and is specifically tailored for using frozen brain tumor tissue.

A versatile and efficient method to isolate nuclei from low-input cryopreserved tissues for single-nuclei transcriptomics

Clinical samples are vital for understanding diseases, but their scarcity requires refined research methods. Emerging single-cell technologies offer detailed views of tissue heterogeneity but need sufficient fully characterized tissues. We developed an optimized single-nuclei RNA sequencing (snRNA-seq) protocol to extract nuclei from just 15 mg of cryopreserved human tissue. Applied to four cancer tissues (brain, bladder, lung, prostate), it profiled 1550-7468 nuclei per tissue, revealing heterogeneity comparable to public single-cell atlases. This method enhances the use and sharing of rare, cryopreserved biospecimens, supporting research where sample quantity is limited and full tissue characterization is needed.

Uncovering the chromatin-mediated transcriptional regulatory network governing cold stress responses in fish immune cells

Temperature fluctuations challenge ectothermic species, particularly tropical fish dependent on external temperatures for physiological regulation. However, the molecular mechanisms through which low-temperature stress impacts immune responses in these species, especially in relation to chromatin accessibility and epigenetic regulation, remain poorly understood. In this study, we investigate chromatin and transcriptional changes in the head kidney and thymus tissues of Nile tilapia (Oreochromis niloticus), a tropical fish of significant economic importance, under cold stress. By analyzing cis-regulatory elements in open chromatin regions and their associated transcription factors (TFs), we construct a comprehensive transcriptional regulatory network (TRN) governing immune responses, including DNA damage-induced apoptosis. Our analysis identifies 119 TFs within the TRN, with Stat1 emerging as a central hub exhibiting distinct binding dynamics under cold stress, as revealed by footprint analysis. Overexpression of Stat1 in immune cells leads to apoptosis and increases the expression of apoptosis-related genes, many of which contain Stat1 binding sites in their regulatory regions, emphasizing its critical role in immune cell survival during cold stress. These results provide insights into the transcriptional and epigenetic regulation of immune responses to cold stress in tilapia and highlight Stat1 as a promising target for enhancing cold tolerance in tropical fish species.

scGO: interpretable deep neural network for cell status annotation and disease diagnosis

Machine learning has emerged as a transformative tool for elucidating cellular heterogeneity in single-cell RNA sequencing. However, a significant challenge lies in the "black box" nature of deep learning models, which obscures the decision-making process and limits interpretability in cell status annotation. In this study, we introduced scGO, a Gene Ontology (GO)-inspired deep learning framework designed to provide interpretable cell status annotation for scRNA-seq data. scGO employs sparse neural networks to leverage the intrinsic biological relationships among genes, transcription factors, and GO terms, significantly augmenting interpretability and reducing computational cost. scGO outperforms state-of-the-art methods in the precise characterization of cell subtypes across diverse datasets. Our extensive experimentation across a spectrum of scRNA-seq datasets underscored the remarkable efficacy of scGO in disease diagnosis, prediction of developmental stages, and evaluation of disease severity and cellular senescence status. Furthermore, we incorporated in silico individual gene manipulations into the scGO model, introducing an additional layer for discovering therapeutic targets. Our results provide an interpretable model for accurately annotating cell status, capturing latent biological knowledge, and informing clinical practice.

Understanding isoform expression by pairing long-read sequencing with single-cell and spatial transcriptomics

RNA isoform diversity, produced via alternative splicing, and alternative usage of transcription start and poly(A) sites, results in varied transcripts being derived from the same gene. Distinct isoforms can play important biological roles, including by changing the sequences or expression levels of protein products. The first single-cell approaches to RNA sequencing-and later, spatial approaches-which are now widely used for the identification of differentially expressed genes, rely on short reads and offer the ability to transcriptomically compare different cell types but are limited in their ability to measure differential isoform expression. More recently, long-read sequencing methods have been combined with single-cell and spatial technologies in order to characterize isoform expression. In this review, we provide an overview of the emergence of single-cell and spatial long-read sequencing and discuss the challenges associated with the implementation of these technologies and interpretation of these data. We discuss the opportunities they offer for understanding the relationships between the distinct variable elements of transcript molecules and highlight some of the ways in which they have been used to characterize isoforms' roles in development and pathology. Single-nucleus long-read sequencing, a special case of the single-cell approach, is also discussed. We attempt to cover both the limitations of these technologies and their significant potential for expanding our still-limited understanding of the biological roles of RNA isoforms.

Single-Cell RNA Sequencing and Combinatorial Approaches for Understanding Heart Biology and Disease

By directly measuring multiple molecular features in hundreds to millions of single cells, single-cell techniques allow for comprehensive characterization of the diversity of cells in the heart. These single-cell transcriptome and multi-omic studies are transforming our understanding of heart development and disease. Compared with single-dimensional inspections, the combination of transcriptomes with spatial dimensions and other omics can provide a comprehensive understanding of single-cell functions, microenvironment, dynamic processes, and their interrelationships. In this review, we will introduce the latest advances in cardiac health and disease at single-cell resolution; single-cell detection methods that can be used for transcriptome, genome, epigenome, and proteome analysis; single-cell multi-omics; as well as their future application prospects.

starTracer is an accelerated approach for precise marker gene identification in single-cell RNA-Seq analysis

Revealing the heterogeneity among tissues is the greatest advantage of single-cell-sequencing. Marker genes not only act as the key to correctly identify cell types, but also the bio-markers for cell-status under certain experimental imputations. Current analysis methods such as Seurat and Monocle employ algorithms which compares one cluster to all the rest and select markers according to statistical tests. This pattern brings redundant calculations and thus, results in low calculation efficiency, specificity and accuracy. To address these issues, we introduce starTracer, a novel algorithm designed to enhance the efficiency, specificity and accuracy of marker gene identification in single-cell RNA-seq data analysis. starTracer operates as an independent pipeline, which exhibits great flexibility by accepting multiple input file types. The primary output is a marker matrix, where genes are sorted by the potential to function as markers, with those exhibiting the greatest potential positioned at the top. The speed improvement ranges by 2 ~ 3 orders of magnitude compared to Seurat, as observed across three independent datasets with lower false positive rate as observed in a simulated testing dataset with ground-truth. It's worth noting that starTracer exhibits increasing speed improvement with larger data volumes. It also excels in identifying markers in smaller clusters. These advantages solidify starTracer as an important tool for single-cell RNA-seq data, merging robust accuracy with exceptional speed.

Histone variant H2BE enhances chromatin accessibility in neurons to promote synaptic gene expression and long-term memory

Histone proteins affect gene expression through multiple mechanisms, including through exchange with histone variants. Recent findings link histone variants to neurological disorders, yet few are well studied in the brain. Most notably, widely expressed variants of H2B remain elusive. We applied recently developed antibodies, biochemical assays, and sequencing approaches to reveal broad expression of the H2B variant H2BE and defined its role in regulating chromatin structure, neuronal transcription, and mouse behavior. We find that H2BE is enriched at promoters, and a single unique amino acid allows it to dramatically enhance chromatin accessibility. Further, we show that H2BE is critical for synaptic gene expression and long-term memory. Together, these data reveal a mechanism linking histone variants to chromatin accessibility, transcriptional regulation, neuronal function, and memory. This work further identifies a widely expressed H2B variant and uncovers a single histone amino acid with profound effects on genomic structure.

Histone variant H2BE enhances chromatin accessibility in neurons to promote synaptic gene expression and long-term memory

Regulation of histone proteins affects gene expression through multiple mechanisms including exchange with histone variants. However, widely expressed variants of H2B remain elusive. Recent findings link histone variants to neurological disorders, yet few are well studied in the brain. We applied new tools including novel antibodies, biochemical assays, and sequencing approaches to reveal broad expression of the H2B variant H2BE, and defined its role in regulating chromatin structure, neuronal transcription, and mouse behavior. We find that H2BE is enriched at promoters and a single unique amino acid allows it to dramatically enhance chromatin accessibility. Lastly, we show that H2BE is critical for synaptic gene expression and long-term memory. Together, these data reveal a novel mechanism linking histone variants to chromatin regulation, neuronal function, and memory. This work further identifies the first widely expressed H2B variant and uncovers a single histone amino acid with profound effects on genomic structure.

Joint single-cell profiling resolves 5mC and 5hmC and reveals their distinct gene regulatory effects

Oxidative modification of 5-methylcytosine (5mC) by ten-eleven translocation (TET) DNA dioxygenases generates 5-hydroxymethylcytosine (5hmC), the most abundant form of oxidized 5mC. Existing single-cell bisulfite sequencing methods cannot resolve 5mC and 5hmC, leaving the cell-type-specific regulatory mechanisms of TET and 5hmC largely unknown. Here, we present joint single-nucleus (hydroxy)methylcytosine sequencing (Joint-snhmC-seq), a scalable and quantitative approach that simultaneously profiles 5hmC and true 5mC in single cells by harnessing differential deaminase activity of APOBEC3A toward 5mC and chemically protected 5hmC. Joint-snhmC-seq profiling of single nuclei from mouse brains reveals an unprecedented level of epigenetic heterogeneity of both 5hmC and true 5mC at single-cell resolution. We show that cell-type-specific profiles of 5hmC or true 5mC improve multimodal single-cell data integration, enable accurate identification of neuronal subtypes and uncover context-specific regulatory effects on cell-type-specific genes by TET enzymes.

Single-nucleus RNA-seq identifies one galanin neuronal subtype in mouse preoptic hypothalamus activated during recovery from sleep deprivation

The preoptic area of the hypothalamus (POA) is essential for sleep regulation. However, the cellular makeup of the POA is heterogeneous, and the molecular identities of the sleep-promoting cells remain elusive. To address this question, this study compares mice during recovery sleep following sleep deprivation to mice allowed extended sleep. Single-nucleus RNA sequencing (single-nucleus RNA-seq) identifies one galanin inhibitory neuronal subtype that shows upregulation of rapid and delayed activity-regulated genes during recovery sleep. This cell type expresses higher levels of growth hormone receptor and lower levels of estrogen receptor compared to other galanin subtypes. single-nucleus RNA-seq also reveals cell-type-specific upregulation of purinergic receptor (P2ry14) and serotonin receptor (Htr2a) during recovery sleep in this neuronal subtype, suggesting possible mechanisms for sleep regulation. Studies with RNAscope validate the single-nucleus RNA-seq findings. Thus, the combined use of single-nucleus RNA-seq and activity-regulated genes identifies a neuronal subtype functionally involved in sleep regulation.

NKX2-2 based nuclei sorting on frozen human archival pancreas enables the enrichment of islet endocrine populations for single-nucleus RNA sequencing

BACKGROUND

Current approaches to profile the single-cell transcriptomics of human pancreatic endocrine cells almost exclusively rely on freshly isolated islets. However, human islets are limited in availability. Furthermore, the extensive processing steps during islet isolation and subsequent single cell dissolution might alter gene expressions. In this work, we report the development of a single-nucleus RNA sequencing (snRNA-seq) approach with targeted islet cell enrichment for endocrine-population focused transcriptomic profiling using frozen archival pancreatic tissues without islet isolation.

RESULTS

We cross-compared five nuclei isolation protocols and selected the citric acid method as the best strategy to isolate nuclei with high RNA integrity and low cytoplasmic contamination from frozen archival human pancreata. We innovated fluorescence-activated nuclei sorting based on the positive signal of NKX2-2 antibody to enrich nuclei of the endocrine population from the entire nuclei pool of the pancreas. Our sample preparation procedure generated high-quality single-nucleus gene-expression libraries while preserving the endocrine population diversity. In comparison with single-cell RNA sequencing (scRNA-seq) library generated with live cells from freshly isolated human islets, the snRNA-seq library displayed comparable endocrine cellular composition and cell type signature gene expression. However, between these two types of libraries, differential enrichments of transcripts belonging to different functional classes could be observed.

CONCLUSIONS

Our work fills a technological gap and helps to unleash frozen archival pancreatic tissues for molecular profiling targeting the endocrine population. This study opens doors to retrospective mappings of endocrine cell dynamics in pancreatic tissues of complex histopathology. We expect that our protocol is applicable to enrich nuclei for transcriptomics studies from various populations in different types of frozen archival tissues.

Single-nucleus RNA and multiomics in situ pairwise sequencing reveals cellular heterogeneity of the abnormal ligamentum teres in patients with developmental dysplasia of the hip

Developmental dysplasia of the hip (DDH) is the most common hip deformity in pediatric orthopedics. One of the common pathological changes in DDH is the thickening and hypertrophy of the ligamentum teres. However, the underlying pathogenic mechanism responsible for these changes remains unclear. This study represents the first time that the heterogeneity of cell subsets in the abnormal ligamentum teres of patients with DDH has been resolved at the single-cell and spatial levels by snRNA-Seq and MiP-Seq. Through gene set enrichment and intercellular communication network analyses, we found that receptor-like cells and ligament stem cells may play an essential role in the pathological changes resulting in ligamentum teres thickening and hypertrophy. Eight ligand-receptor pairs related to the ECM-receptor pathway were observed to be closely associated with DDH. Further, using the Monocle R package, we predicted a differentiation trajectory of pericytes into two branches, leading to junctional ligament stem cells or fibroblasts. The expression of extracellular matrix-related genes along pseudotemporal trajectories was also investigated. Using MiP-Seq, we determined the expression distribution of marker genes specific to different cell types within the ligamentum teres, as well as differentially expressed DDH-associated genes at the spatial level.

Differences in molecular sampling and data processing explain variation among single-cell and single-nucleus RNA-seq experiments

A mechanistic understanding of the biological and technical factors that impact transcript measurements is essential to designing and analyzing single-cell and single-nucleus RNA sequencing experiments. Nuclei contain the same pre-mRNA population as cells, but they contain a small subset of the mRNAs. Nonetheless, early studies argued that single-nucleus analysis yielded results comparable to cellular samples if pre-mRNA measurements were included. However, typical workflows do not distinguish between pre-mRNA and mRNA when estimating gene expression, and variation in their relative abundances across cell types has received limited attention. These gaps are especially important given that incorporating pre-mRNA has become commonplace for both assays, despite known gene length bias in pre-mRNA capture. Here, we reanalyze public data sets from mouse and human to describe the mechanisms and contrasting effects of mRNA and pre-mRNA sampling on gene expression and marker gene selection in single-cell and single-nucleus RNA-seq. We show that pre-mRNA levels vary considerably among cell types, which mediates the degree of gene length bias and limits the generalizability of a recently published normalization method intended to correct for this bias. As an alternative, we repurpose an existing post hoc gene length-based correction method from conventional RNA-seq gene set enrichment analysis. Finally, we show that inclusion of pre-mRNA in bioinformatic processing can impart a larger effect than assay choice itself, which is pivotal to the effective reuse of existing data. These analyses advance our understanding of the sources of variation in single-cell and single-nucleus RNA-seq experiments and provide useful guidance for future studies.

A topographical atlas of α-synuclein dosage and cell type-specific expression in adult mouse brain and peripheral organs

Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide and presents pathologically with Lewy pathology and dopaminergic neurodegeneration. Lewy pathology contains aggregated α-synuclein (αSyn), a protein encoded by the SNCA gene which is also mutated or duplicated in a subset of familial PD cases. Due to its predominant presynaptic localization, immunostaining for the protein results in a diffuse reactivity pattern, providing little insight into the types of cells expressing αSyn. As a result, insight into αSyn expression-driven cellular vulnerability has been difficult to ascertain. Using a combination of knock-in mice that target αSyn to the nucleus (SncaNLS) and in situ hybridization of Snca in wild-type mice, we systematically mapped the topography and cell types expressing αSyn in the mouse brain, spinal cord, retina, and gut. We find a high degree of correlation between αSyn protein and RNA levels and further identify cell types with low and high αSyn content. We also find high αSyn expression in neurons, particularly those involved in PD, and to a lower extent in non-neuronal cell types, notably those of oligodendrocyte lineage, which are relevant to multiple system atrophy pathogenesis. Surprisingly, we also found that αSyn is relatively absent from select neuron types, e.g., ChAT-positive motor neurons, whereas enteric neurons universally express some degree of αSyn. Together, this integrated atlas provides insight into the cellular topography of αSyn, and provides a quantitative map to test hypotheses about the role of αSyn in network vulnerability, and thus serves investigations into PD pathogenesis and other α-synucleinopathies.

Using deep learning to quantify neuronal activation from single-cell and spatial transcriptomic data

Neuronal activity-dependent transcription directs molecular processes that regulate synaptic plasticity, brain circuit development, behavioral adaptation, and long-term memory. Single cell RNA-sequencing technologies (scRNAseq) are rapidly developing and allow for the interrogation of activity-dependent transcription at cellular resolution. Here, we present NEUROeSTIMator, a deep learning model that integrates transcriptomic signals to estimate neuronal activation in a way that we demonstrate is associated with Patch-seq electrophysiological features and that is robust against differences in species, cell type, and brain region. We demonstrate this method's ability to accurately detect neuronal activity in previously published studies of single cell activity-induced gene expression. Further, we applied our model in a spatial transcriptomic study to identify unique patterns of learning-induced activity across different brain regions in male mice. Altogether, our findings establish NEUROeSTIMator as a powerful and broadly applicable tool for measuring neuronal activation, whether as a critical covariate or a primary readout of interest.

Self-supervised deep learning of gene-gene interactions for improved gene expression recovery

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to gain biological insights at the cellular level. However, due to technical limitations of the existing sequencing technologies, low gene expression values are often omitted, leading to inaccurate gene counts. Existing methods, including advanced deep learning techniques, struggle to reliably impute gene expressions due to a lack of mechanisms that explicitly consider the underlying biological knowledge of the system. In reality, it has long been recognized that gene-gene interactions may serve as reflective indicators of underlying biology processes, presenting discriminative signatures of the cells. A genomic data analysis framework that is capable of leveraging the underlying gene-gene interactions is thus highly desirable and could allow for more reliable identification of distinctive patterns of the genomic data through extraction and integration of intricate biological characteristics of the genomic data. Here we tackle the problem in two steps to exploit the gene-gene interactions of the system. We first reposition the genes into a 2D grid such that their spatial configuration reflects their interactive relationships. To alleviate the need for labeled ground truth gene expression datasets, a self-supervised 2D convolutional neural network is employed to extract the contextual features of the interactions from the spatially configured genes and impute the omitted values. Extensive experiments with both simulated and experimental scRNA-seq datasets are carried out to demonstrate the superior performance of the proposed strategy against the existing imputation methods.

Sweat gland development requires an eccrine dermal niche and couples two epidermal programs

Eccrine sweat glands are indispensable for human thermoregulation and, similar to other mammalian skin appendages, form from multipotent epidermal progenitors. Limited understanding of how epidermal progenitors specialize to form these vital organs has precluded therapeutic efforts toward their regeneration. Herein, we applied single-nucleus transcriptomics to compare the expression content of wild-type, eccrine-forming mouse skin to that of mice harboring a skin-specific disruption of Engrailed 1 (En1), a transcription factor that promotes eccrine gland formation in humans and mice. We identify two concurrent but disproportionate epidermal transcriptomes in the early eccrine anlagen: one that is shared with hair follicles and one that is En1 dependent and eccrine specific. We demonstrate that eccrine development requires the induction of a dermal niche proximal to each developing gland in humans and mice. Our study defines the signatures of eccrine identity and uncovers the eccrine dermal niche, setting the stage for targeted regeneration and comprehensive skin repair.

Choroid plexus mast cells drive tumor-associated hydrocephalus

Tumor-associated hydrocephalus (TAH) is a common and lethal complication of brain metastases. Although other factors beyond mechanical obstructions have been suggested, the exact mechanisms are unknown. Using single-nucleus RNA sequencing and spatial transcriptomics, we find that a distinct population of mast cells locate in the choroid plexus and dramatically increase during TAH. Genetic fate tracing and intracranial mast-cell-specific tryptase knockout showed that choroid plexus mast cells (CPMCs) disrupt cilia of choroid plexus epithelia via the tryptase-PAR2-FoxJ1 pathway and consequently increase cerebrospinal fluid production. Mast cells are also found in the human choroid plexus. Levels of tryptase in cerebrospinal fluid are closely associated with clinical severity of TAH. BMS-262084, an inhibitor of tryptase, can cross the blood-brain barrier, inhibit TAH in vivo, and alleviate mast-cell-induced damage of epithelial cilia in a human pluripotent stem-cell-derived choroid plexus organoid model. Collectively, we uncover the function of CPMCs and provide an attractive therapy for TAH.

Deep scRNA sequencing reveals a broadly applicable Regeneration Classifier and implicates antioxidant response in corticospinal axon regeneration

Despite substantial progress in understanding the biology of axon regeneration in the CNS, our ability to promote regeneration of the clinically important corticospinal tract (CST) after spinal cord injury remains limited. To understand regenerative heterogeneity, we conducted patch-based single-cell RNA sequencing on rare regenerating CST neurons at high depth following PTEN and SOCS3 deletion. Supervised classification with Garnett gave rise to a Regeneration Classifier, which can be broadly applied to predict the regenerative potential of diverse neuronal types across developmental stages or after injury. Network analyses highlighted the importance of antioxidant response and mitochondrial biogenesis. Conditional gene deletion validated a role for NFE2L2 (or NRF2), a master regulator of antioxidant response, in CST regeneration. Our data demonstrate a universal transcriptomic signature underlying the regenerative potential of vastly different neuronal populations and illustrate that deep sequencing of only hundreds of phenotypically identified neurons has the power to advance regenerative biology.

Sample enrichment for single-nucleus sequencing using concanavalin A-conjugated magnetic beads

Single-cell/nucleus sequencing has been increasingly used to study specific cell populations. However, cells/nuclei often become diluted during isolation steps and are difficult to reconcentrate through centrifugation. Here, we present a protocol for sample enrichment using concanavalin A-conjugated magnetic beads. We describe steps for dissection, nuclei isolation, and fluorescence-activated cell sorting (FACS). We then detail procedures for nuclei enrichment and library preparation. This protocol enables efficient retrieval and enrichment of cells/nuclei following FACS and integrates into existing workflows of various 10× Genomics applications.

NAD+ rescues aging-induced blood-brain barrier damage via the CX43-PARP1 axis

Blood-brain barrier (BBB) function deteriorates during aging, contributing to cognitive impairment and neurodegeneration. It is unclear what drives BBB leakage in aging and how it can be prevented. Using single-nucleus transcriptomics, we identified decreased connexin 43 (CX43) expression in cadherin-5+ (Cdh5+) cerebral vascular cells in naturally aging mice and confirmed it in human brain samples. Global or Cdh5+ cell-specific CX43 deletion in mice exacerbated BBB dysfunction during aging. The CX43-dependent effect was not due to its canonical gap junction function but was associated with reduced NAD+ levels and mitochondrial dysfunction through NAD+-dependent sirtuin 3 (SIRT3). CX43 interacts with and negatively regulates poly(ADP-ribose) polymerase 1 (PARP1). Pharmacologic inhibition of PARP1 by olaparib or nicotinamide mononucleotide (NMN) supplementation rescued NAD+ levels and alleviated aging-associated BBB leakage. These findings establish the endothelial CX43-PARP1-NAD+ pathway's role in vascular aging and identify a potential therapeutic strategy to combat aging-associated BBB leakage with neuroprotective implications.

Ultra-Deep Sequencing Reveals the Mutational Landscape of Classical Hodgkin Lymphoma

The malignant Hodgkin and Reed Sternberg (HRS) cells of classical Hodgkin lymphoma (cHL) are scarce in affected lymph nodes, creating a challenge to detect driver somatic mutations. As an alternative to cell purification techniques, we hypothesized that ultra-deep exome sequencing would allow genomic study of HRS cells, thereby streamlining analysis and avoiding technical pitfalls. To test this, 31 cHL tumor/normal pairs were exome sequenced to approximately 1,000× median depth of coverage. An orthogonal error-corrected sequencing approach verified >95% of the discovered mutations. We identified mutations in genes novel to cHL including: CDH5 and PCDH7, novel stop gain mutations in IL4R, and a novel pattern of recurrent mutations in pathways regulating Hippo signaling. As a further application of our exome sequencing, we attempted to identify expressed somatic single-nucleotide variants (SNV) in single-nuclei RNA sequencing (snRNA-seq) data generated from a patient in our cohort. Our snRNA analysis identified a clear cluster of cells containing a somatic SNV identified in our deep exome data. This cluster has differentially expressed genes that are consistent with genes known to be dysregulated in HRS cells (e.g., PIM1 and PIM3). The cluster also contains cells with an expanded B-cell clonotype further supporting a malignant phenotype. This study provides proof-of-principle that ultra-deep exome sequencing can be utilized to identify recurrent mutations in HRS cells and demonstrates the feasibility of snRNA-seq in the context of cHL. These studies provide the foundation for the further analysis of genomic variants in large cohorts of patients with cHL.

SIGNIFICANCE

Our data demonstrate the utility of ultra-deep exome sequencing in uncovering somatic variants in Hodgkin lymphoma, creating new opportunities to define the genes that are recurrently mutated in this disease. We also show for the first time the successful application of snRNA-seq in Hodgkin lymphoma and describe the expression profile of a putative cluster of HRS cells in a single patient.

Temporally specific gene expression and chromatin remodeling programs regulate a conserved Pdyn enhancer

Neuronal and behavioral adaptations to novel stimuli are regulated by temporally dynamic waves of transcriptional activity, which shape neuronal function and guide enduring plasticity. Neuronal activation promotes expression of an immediate early gene (IEG) program comprised primarily of activity-dependent transcription factors, which are thought to regulate a second set of late response genes (LRGs). However, while the mechanisms governing IEG activation have been well studied, the molecular interplay between IEGs and LRGs remain poorly characterized. Here, we used transcriptomic and chromatin accessibility profiling to define activity-driven responses in rat striatal neurons. As expected, neuronal depolarization generated robust changes in gene expression, with early changes (1 hr) enriched for inducible transcription factors and later changes (4 hr) enriched for neuropeptides, synaptic proteins, and ion channels. Remarkably, while depolarization did not induce chromatin remodeling after 1 hr, we found broad increases in chromatin accessibility at thousands of sites in the genome at 4 hr after neuronal stimulation. These putative regulatory elements were found almost exclusively at non-coding regions of the genome, and harbored consensus motifs for numerous activity-dependent transcription factors such as AP-1. Furthermore, blocking protein synthesis prevented activity-dependent chromatin remodeling, suggesting that IEG proteins are required for this process. Targeted analysis of LRG loci identified a putative enhancer upstream of Pdyn (prodynorphin), a gene encoding an opioid neuropeptide implicated in motivated behavior and neuropsychiatric disease states. CRISPR-based functional assays demonstrated that this enhancer is both necessary and sufficient for Pdyn transcription. This regulatory element is also conserved at the human PDYN locus, where its activation is sufficient to drive PDYN transcription in human cells. These results suggest that IEGs participate in chromatin remodeling at enhancers and identify a conserved enhancer that may act as a therapeutic target for brain disorders involving dysregulation of Pdyn.

Tissue morphology influences the temporal program of human brain organoid development

Progression through fate decisions determines cellular composition and tissue architecture, but how that same architecture may impact cell fate is less clear. We took advantage of organoids as a tractable model to interrogate this interaction of form and fate. Screening methodological variations revealed that common protocol adjustments impacted various aspects of morphology, from macrostructure to tissue architecture. We examined the impact of morphological perturbations on cell fate through integrated single nuclear RNA sequencing (snRNA-seq) and spatial transcriptomics. Regardless of the specific protocol, organoids with more complex morphology better mimicked in vivo human fetal brain development. Organoids with perturbed tissue architecture displayed aberrant temporal progression, with cells being intermingled in both space and time. Finally, encapsulation to impart a simplified morphology led to disrupted tissue cytoarchitecture and a similar abnormal maturational timing. These data demonstrate that cells of the developing brain require proper spatial coordinates to undergo correct temporal progression.

Droplet-based transcriptome profiling of individual synapses

Synapses are crucial structures that mediate signal transmission between neurons in complex neural circuits and display considerable morphological and electrophysiological heterogeneity. So far we still lack a high-throughput method to profile the molecular heterogeneity among individual synapses. In the present study, we develop a droplet-based single-cell (sc) total-RNA-sequencing platform, called Multiple-Annealing-and-Tailing-based Quantitative scRNA-seq in Droplets, for transcriptome profiling of individual neurites, primarily composed of synaptosomes. In the synaptosome transcriptome, or 'synaptome', profiling of both mouse and human brain samples, we detect subclusters among synaptosomes that are associated with neuronal subtypes and characterize the landscape of transcript splicing that occurs within synapses. We extend synaptome profiling to synaptopathy in an Alzheimer's disease (AD) mouse model and discover AD-associated synaptic gene expression changes that cannot be detected by single-nucleus transcriptome profiling. Overall, our results show that this platform provides a high-throughput, single-synaptosome transcriptome profiling tool that will facilitate future discoveries in neuroscience.

Activity-regulated gene expression across cell types of the mouse hippocampus

Activity-regulated gene (ARG) expression patterns in the hippocampus (HPC) regulate synaptic plasticity, learning, and memory, and are linked to both risk and treatment responses for many neuropsychiatric disorders. The HPC contains discrete classes of neurons with specialized functions, but cell type-specific activity-regulated transcriptional programs are not well characterized. Here, we used single-nucleus RNA-sequencing (snRNA-seq) in a mouse model of acute electroconvulsive seizures (ECS) to identify cell type-specific molecular signatures associated with induced activity in HPC neurons. We used unsupervised clustering and a priori marker genes to computationally annotate 15,990 high-quality HPC neuronal nuclei from N = 4 mice across all major HPC subregions and neuron types. Activity-induced transcriptomic responses were divergent across neuron populations, with dentate granule cells being particularly responsive to activity. Differential expression analysis identified both upregulated and downregulated cell type-specific gene sets in neurons following ECS. Within these gene sets, we identified enrichment of pathways associated with varying biological processes such as synapse organization, cellular signaling, and transcriptional regulation. Finally, we used matrix factorization to reveal continuous gene expression patterns differentially associated with cell type, ECS, and biological processes. This work provides a rich resource for interrogating activity-regulated transcriptional responses in HPC neurons at single-nuclei resolution in the context of ECS, which can provide biological insight into the roles of defined neuronal subtypes in HPC function.

Erythropoietin re-wires cognition-associated transcriptional networks

Recombinant human erythropoietin (rhEPO) has potent procognitive effects, likely hematopoiesis-independent, but underlying mechanisms and physiological role of brain-expressed EPO remained obscure. Here, we provide transcriptional hippocampal profiling of male mice treated with rhEPO. Based on ~108,000 single nuclei, we unmask multiple pyramidal lineages with their comprehensive molecular signatures. By temporal profiling and gene regulatory analysis, we build developmental trajectory of CA1 pyramidal neurons derived from multiple predecessor lineages and elucidate gene regulatory networks underlying their fate determination. With EPO as 'tool', we discover populations of newly differentiating pyramidal neurons, overpopulating to ~200% upon rhEPO with upregulation of genes crucial for neurodifferentiation, dendrite growth, synaptogenesis, memory formation, and cognition. Using a Cre-based approach to visually distinguish pre-existing from newly formed pyramidal neurons for patch-clamp recordings, we learn that rhEPO treatment differentially affects excitatory and inhibitory inputs. Our findings provide mechanistic insight into how EPO modulates neuronal functions and networks.

ASIC1a affects hypothalamic signaling and regulates the daily rhythm of body temperature in mice

The body temperature of mice is higher at night than during the day. We show here that global deletion of acid-sensing ion channel 1a (ASIC1a) results in lower body temperature during a part of the night. ASICs are pH sensors that modulate neuronal activity. The deletion of ASIC1a decreased the voluntary activity at night of mice that had access to a running wheel but did not affect their spontaneous activity. Daily rhythms of thyrotropin-releasing hormone mRNA in the hypothalamus and of thyroid-stimulating hormone β mRNA in the pituitary, and of prolactin mRNA in the hypothalamus and pituitary were suppressed in ASIC1a-/- mice. The serum thyroid hormone levels were however not significantly changed by ASIC1a deletion. Our findings indicate that ASIC1a regulates activity and signaling in the hypothalamus and pituitary. This likely leads to the observed changes in body temperature by affecting the metabolism or energy expenditure.

High-throughput single nucleus total RNA sequencing of formalin-fixed paraffin-embedded tissues by snRandom-seq

Formalin-fixed paraffin-embedded (FFPE) tissues constitute a vast and valuable patient material bank for clinical history and follow-up data. It is still challenging to achieve single cell/nucleus RNA (sc/snRNA) profile in FFPE tissues. Here, we develop a droplet-based snRNA sequencing technology (snRandom-seq) for FFPE tissues by capturing full-length total RNAs with random primers. snRandom-seq shows a minor doublet rate (0.3%), a much higher RNA coverage, and detects more non-coding RNAs and nascent RNAs, compared with state-of-art high-throughput scRNA-seq technologies. snRandom-seq detects a median of >3000 genes per nucleus and identifies 25 typical cell types. Moreover, we apply snRandom-seq on a clinical FFPE human liver cancer specimen and reveal an interesting subpopulation of nuclei with high proliferative activity. Our method provides a powerful snRNA-seq platform for clinical FFPE specimens and promises enormous applications in biomedical research.

Cellular Diversity in Human Subgenual Anterior Cingulate and Dorsolateral Prefrontal Cortex by Single-Nucleus RNA-Sequencing

Regional cellular heterogeneity is a fundamental feature of the human neocortex; however, details of this heterogeneity are still undefined. We used single-nucleus RNA-sequencing to examine cell-specific transcriptional features in the dorsolateral PFC (DLPFC) and the subgenual anterior cingulate cortex (sgACC), regions implicated in major psychiatric disorders. Droplet-based nuclei-capture and library preparation were performed on replicate samples from 8 male donors without history of psychiatric or neurologic disorder. Unsupervised clustering identified major neural cell classes. Subsequent iterative clustering of neurons further revealed 20 excitatory and 22 inhibitory subclasses. Inhibitory cells were consistently more abundant in the sgACC and excitatory neuron subclusters exhibited considerable variability across brain regions. Excitatory cell subclasses also exhibited greater within-class transcriptional differences between the two regions. We used these molecular definitions to determine which cell classes might be enriched in loci carrying a genetic signal in genome-wide association studies or for differentially expressed genes in mental illness. We found that the heritable signals of psychiatric disorders were enriched in neurons and that, while the gene expression changes detected in bulk-RNA-sequencing studies were dominated by glial cells, some alterations could be identified in specific classes of excitatory and inhibitory neurons. Intriguingly, only two excitatory cell classes exhibited concomitant region-specific enrichment for both genome-wide association study loci and transcriptional dysregulation. In sum, by detailing the molecular and cellular diversity of the DLPFC and sgACC, we were able to generate hypotheses on regional and cell-specific dysfunctions that may contribute to the development of mental illness.SIGNIFICANCE STATEMENT Dysfunction of the subgenual anterior cingulate cortex has been implicated in mood disorders, particularly major depressive disorder, and the dorsolateral PFC, a subsection of the PFC involved in executive functioning, has been implicated in schizophrenia. Understanding the cellular composition of these regions is critical to elucidating the neurobiology underlying psychiatric and neurologic disorders. We studied cell type diversity of the subgenual anterior cingulate cortex and dorsolateral PFC of humans with no neuropsychiatric illness using a clustering analysis of single-nuclei RNA-sequencing data. Defining the transcriptomic profile of cellular subpopulations in these cortical regions is a first step to demystifying the cellular and molecular pathways involved in psychiatric disorders.

Molecular encoding of stimulus features in a single sensory neuron type enables neuronal and behavioral plasticity

Neurons modify their transcriptomes in response to an animal's experience. How specific experiences are transduced to modulate gene expression and precisely tune neuronal functions are not fully defined. Here, we describe the molecular profile of a thermosensory neuron pair in C. elegans experiencing different temperature stimuli. We find that distinct salient features of the temperature stimulus, including its duration, magnitude of change, and absolute value, are encoded in the gene expression program in this single neuron type, and we identify a novel transmembrane protein and a transcription factor whose specific transcriptional dynamics are essential to drive neuronal, behavioral, and developmental plasticity. Expression changes are driven by broadly expressed activity-dependent transcription factors and corresponding cis-regulatory elements that nevertheless direct neuron- and stimulus-specific gene expression programs. Our results indicate that coupling of defined stimulus characteristics to the gene regulatory logic in individual specialized neuron types can customize neuronal properties to drive precise behavioral adaptation.

Molecular encoding of stimulus features in a single sensory neuron type enables neuronal and behavioral plasticity

Neurons modify their transcriptomes in response to an animal’s experience. How specific experiences are transduced to modulate gene expression and precisely tune neuronal functions are not fully defined. Here, we describe the molecular profile of a thermosensory neuron pair in C. elegans experiencing different temperature stimuli. We find that distinct salient features of the temperature stimulus including its duration, magnitude of change, and absolute value are encoded in the gene expression program in this single neuron, and identify a novel transmembrane protein and a transcription factor whose specific transcriptional dynamics are essential to drive neuronal, behavioral, and developmental plasticity. Expression changes are driven by broadly expressed activity-dependent transcription factors and corresponding cis -regulatory elements that nevertheless direct neuron- and stimulus-specific gene expression programs. Our results indicate that coupling of defined stimulus characteristics to the gene regulatory logic in individual specialized neuron types can customize neuronal properties to drive precise behavioral adaptation.

Recent advances in understanding neuronal diversity and neural circuit complexity across different brain regions using single-cell sequencing

Neural circuits are characterized as interconnecting neuron networks connected by synapses. Some kinds of gene expression and/or functional changes of neurons and synaptic connections may result in aberrant neural circuits, which has been recognized as one crucial pathological mechanism for the onset of many neurological diseases. Gradual advances in single-cell sequencing approaches with strong technological advantages, as exemplified by high throughput and increased resolution for live cells, have enabled it to assist us in understanding neuronal diversity across diverse brain regions and further transformed our knowledge of cellular building blocks of neural circuits through revealing numerous molecular signatures. Currently published transcriptomic studies have elucidated various neuronal subpopulations as well as their distribution across prefrontal cortex, hippocampus, hypothalamus, and dorsal root ganglion, etc. Better characterization of brain region-specific circuits may shed light on new pathological mechanisms involved and assist in selecting potential targets for the prevention and treatment of specific neurological disorders based on their established roles. Given diverse neuronal populations across different brain regions, we aim to give a brief sketch of current progress in understanding neuronal diversity and neural circuit complexity according to their locations. With the special focus on the application of single-cell sequencing, we thereby summarize relevant region-specific findings. Considering the importance of spatial context and connectivity in neural circuits, we also discuss a few published results obtained by spatial transcriptomics. Taken together, these single-cell sequencing data may lay a mechanistic basis for functional identification of brain circuit components, which links their molecular signatures to anatomical regions, connectivity, morphology, and physiology. Furthermore, the comprehensive characterization of neuron subtypes, their distributions, and connectivity patterns via single-cell sequencing is critical for understanding neural circuit properties and how they generate region-dependent interactions in different context.

Leveraging data-driven self-consistency for high-fidelity gene expression recovery

Single cell RNA sequencing is a promising technique to determine the states of individual cells and classify novel cell subtypes. In current sequence data analysis, however, genes with low expressions are omitted, which leads to inaccurate gene counts and hinders downstream analysis. Recovering these omitted expression values presents a challenge because of the large size of the data. Here, we introduce a data-driven gene expression recovery framework, referred to as self-consistent expression recovery machine (SERM), to impute the missing expressions. Using a neural network, the technique first learns the underlying data distribution from a subset of the noisy data. It then recovers the overall expression data by imposing a self-consistency on the expression matrix, thus ensuring that the expression levels are similarly distributed in different parts of the matrix. We show that SERM improves the accuracy of gene imputation with orders of magnitude enhancement in computational efficiency in comparison to the state-of-the-art imputation techniques.

A single-cell transcriptome atlas of glial diversity in the human hippocampus across the postnatal lifespan

The molecular diversity of glia in the human hippocampus and their temporal dynamics over the lifespan remain largely unknown. Here, we performed single-nucleus RNA sequencing to generate a transcriptome atlas of the human hippocampus across the postnatal lifespan. Detailed analyses of astrocytes, oligodendrocyte lineages, and microglia identified subpopulations with distinct molecular signatures and revealed their association with specific physiological functions, age-dependent changes in abundance, and disease relevance. We further characterized spatiotemporal heterogeneity of GFAP-enriched astrocyte subpopulations in the hippocampal formation using immunohistology. Leveraging glial subpopulation classifications as a reference map, we revealed the diversity of glia differentiated from human pluripotent stem cells and identified dysregulated genes and pathological processes in specific glial subpopulations in Alzheimer's disease (AD). Together, our study significantly extends our understanding of human glial diversity, population dynamics across the postnatal lifespan, and dysregulation in AD and provides a reference atlas for stem-cell-based glial differentiation.

Microfluidics for Neuronal Cell and Circuit Engineering

The widespread adoption of microfluidic devices among the neuroscience and neurobiology communities has enabled addressing a broad range of questions at the molecular, cellular, circuit, and system levels. Here, we review biomedical engineering approaches that harness the power of microfluidics for bottom-up generation of neuronal cell types and for the assembly and analysis of neural circuits. Microfluidics-based approaches are instrumental to generate the knowledge necessary for the derivation of diverse neuronal cell types from human pluripotent stem cells, as they enable the isolation and subsequent examination of individual neurons of interest. Moreover, microfluidic devices allow to engineer neural circuits with specific orientations and directionality by providing control over neuronal cell polarity and permitting the isolation of axons in individual microchannels. Similarly, the use of microfluidic chips enables the construction not only of 2D but also of 3D brain, retinal, and peripheral nervous system model circuits. Such brain-on-a-chip and organoid-on-a-chip technologies are promising platforms for studying these organs as they closely recapitulate some aspects of in vivo biological processes. Microfluidic 3D neuronal models, together with 2D in vitro systems, are widely used in many applications ranging from drug development and toxicology studies to neurological disease modeling and personalized medicine. Altogether, microfluidics provide researchers with powerful systems that complement and partially replace animal models.

Corticogenesis across species at single-cell resolution

The neocortex (or pallium) consists of diverse cell types that are organized in a highly species-specific manner under strict spatiotemporal control during development. Many of the cell types are present transiently throughout development but contribute to permanent species-specific cortical features that are acquired through evolution. Therefore, capturing cell type-specific biological information has always been an important quest in the field of neurodevelopment. The progress in achieving fine cellular resolution has been slow due to technical challenges. However, with recent advancements in single-cell and multi-omics technologies, many laboratories have begun to successfully interrogate cellular and molecular mechanisms driving corticogenesis at single-cell resolution. In this review, we provide summarized results from many primary publications and several in-depth review articles that utilize or address single-cell genomics techniques to understand important topics, such as cellular and molecular mechanisms governing cortical progenitor proliferation, cell lineage progression, neuronal specification, and arealization, across multiple gyrencephalic (i.e., human and non-human primates) and lissencephalic species (i.e., mouse, reptiles, and songbirds). We also examine findings from recent studies involving epigenomic and posttranscriptional regulation of corticogenesis. In the discussion section, we provide our insights on the challenges the field currently faces as well as promising future applications of single cell technologies.

All roads lead to heterogeneity: The complex involvement of astrocytes and microglia in the pathogenesis of Alzheimer’s disease

In recent years, glial cells have been acknowledged as key players in the pathogenesis of Alzheimer’s disease (AD), a neurodegenerative condition in which an accumulation of intracellular neurofibrillary tangles and extracellular fibrillar amyloid beta is notably observed in the central nervous system. Genome-wide association studies have shown, both in microglia and astrocytes, an increase in gene variants associated with a higher risk of developing late-onset AD. Microglia, the resident innate immune cells of the brain, and astrocytes, glial cells crucial for vascular integrity and neuronal support, both agglomerate near amyloid beta plaques and dystrophic neurites where they participate in the elimination of these harmful parenchymal elements. However, their role in AD pathogenesis has been challenging to resolve due to the highly heterogeneous nature of these cell populations, i.e., their molecular, morphological, and ultrastructural diversity, together with their ever-changing responsiveness and functions throughout the pathological course of AD. With the recent expansions in the field of glial heterogeneity through innovative advances in state-of-the-art microscopy and -omics techniques, novel concepts and questions arose, notably pertaining to how the diverse microglial and astrocytic states interact with each other and with the AD hallmarks, and how their concerted efforts/actions impact the progression of the disease. In this review, we discuss the recent advances and findings on the topic of glial heterogeneity, particularly focusing on the relationships of these cells with AD hallmarks (e.g., amyloid beta plaques, neurofibrillary tangles, synaptic loss, and dystrophic neurites) in murine models of AD pathology and post-mortem brain samples of patients with AD.

Reconstruction of the Global Polarity of an Early Spider Embryo by Single-Cell and Single-Nucleus Transcriptome Analysis

Patterning along an axis of polarity is a fundamental step in the development of a multicellular animal embryo. In the cellular field of an early spider embryo, Hedgehog signaling operates to specify a "fuzzy" French-flag-like pattern along the primary axis, which is related to the future anterior-posterior (A-P) axis. However, details regarding the generation and development of a diversity of cell states based on the embryo polarity are not known. To address this issue, we applied single-cell RNA sequencing to the early spider embryo consisting of approximately 2,000 cells. Our results confirmed that this technique successfully detected 3 cell populations corresponding to the germ layers and some transient cell states. We showed that the data from dissociated cells had sufficient information for reconstruction of a correct global A-P polarity of the presumptive ectoderm, without clear segregation of specific cell states. This outcome is explained by the varied but differentially overlapping expression of Hedgehog-signal target genes and newly identified marker genes. We also showed that the data resources generated by the transcriptome analysis are applicable to a genome-wide search for genes whose expression is spatially regulated, based on the detection of pattern similarity. Furthermore, we performed single-nucleus RNA sequencing, which was more powerful in detecting emerging cell states. The single-cell and single-nucleus transcriptome techniques will help investigate the pattern-forming processes in the spider model system in an unbiased, comprehensive manner. We provided web-based resources of these transcriptome datasets for future studies of pattern formation and cell differentiation.

Pro-inflammatory cytokines mediate the epithelial-to-mesenchymal-like transition of pediatric posterior fossa ependymoma

Pediatric ependymoma is a devastating brain cancer marked by its relapsing pattern and lack of effective chemotherapies. This shortage of treatments is due to limited knowledge about ependymoma tumorigenic mechanisms. By means of single-nucleus chromatin accessibility and gene expression profiling of posterior fossa primary tumors and distal metastases, we reveal key transcription factors and enhancers associated with the differentiation of ependymoma tumor cells into tumor-derived cell lineages and their transition into a mesenchymal-like state. We identify NFκB, AP-1, and MYC as mediators of this transition, and show that the gene expression profiles of tumor cells and infiltrating microglia are consistent with abundant pro-inflammatory signaling between these populations. In line with these results, both TGF-β1 and TNF-α induce the expression of mesenchymal genes on a patient-derived cell model, and TGF-β1 leads to an invasive phenotype. Altogether, these data suggest that tumor gliosis induced by inflammatory cytokines and oxidative stress underlies the mesenchymal phenotype of posterior fossa ependymoma.

Molecular landscapes of human hippocampal immature neurons across lifespan

Immature dentate granule cells (imGCs) arising from adult hippocampal neurogenesis contribute to plasticity and unique brain functions in rodents1,2 and are dysregulated in multiple human neurological disorders3-5. Little is known about the molecular characteristics of adult human hippocampal imGCs, and even their existence is under debate1,6-8. Here we performed single-nucleus RNA sequencing aided by a validated machine learning-based analytic approach to identify imGCs and quantify their abundance in the human hippocampus at different stages across the lifespan. We identified common molecular hallmarks of human imGCs across the lifespan and observed age-dependent transcriptional dynamics in human imGCs that suggest changes in cellular functionality, niche interactions and disease relevance, that differ from those in mice9. We also found a decreased number of imGCs with altered gene expression in Alzheimer's disease. Finally, we demonstrated the capacity for neurogenesis in the adult human hippocampus with the presence of rare dentate granule cell fate-specific proliferating neural progenitors and with cultured surgical specimens. Together, our findings suggest the presence of a substantial number of imGCs in the adult human hippocampus via low-frequency de novo generation and protracted maturation, and our study reveals their molecular properties across the lifespan and in Alzheimer's disease.

Single-cell atlases: shared and tissue-specific cell types across human organs

The development of single-cell and spatial transcriptomics methods was instrumental in the conception of the Human Cell Atlas initiative, which aims to generate an integrated map of all cells across the human body. These technology advances are bringing increasing depth and resolution to maps of human organs and tissues, as well as our understanding of individual human cell types. Commonalities as well as tissue-specific features of primary and supportive cell types across human organs are beginning to emerge from these human tissue maps. In this Review, we highlight key biological insights obtained from cross-tissue studies into epithelial, fibroblast, vascular and immune cells based on single-cell gene expression data in humans and contrast it with mechanisms reported in mice.

Single-cell multi-omics sequencing and its applications in studying the nervous system

Single-cell sequencing has become one of the most powerful and popular techniques in dissecting molecular heterogeneity and modeling the cellular architecture of a biological system. During the past twenty years, the throughput of single-cell sequencing has increased from hundreds of cells to over tens of thousands of cells in parallel. Moreover, this technology has been developed from sequencing transcriptome to measure different omics such as DNA methylome, chromatin accessibility, and so on. Currently, multi-omics which can analyze different omics in the same cell is rapidly advancing. This work advances the study of many biosystems, including the nervous system. Here, we review current single-cell multi-omics sequencing techniques and describe how they improve our understanding of the nervous system. Finally, we discuss the open scientific questions in neural research that may be answered through further improvement of single-cell multi-omics sequencing technology.

Mapping cis-regulatory elements in human neurons links psychiatric disease heritability and activity-regulated transcriptional programs

Genome-wide association studies (GWASs) have identified hundreds of loci associated with psychiatric diseases, yet there is a lack of understanding of disease pathophysiology. Common risk variants can shed light on the underlying molecular mechanisms; however, identifying causal variants remains challenging. We map cis-regulatory elements in human neurons derived from pluripotent stem cells. This system allows us to determine enhancers that activate the transcription of neuronal activity-regulated gene programs, which are thought to be critical for synaptic plasticity and are not possible to identify from postmortem tissues. Using the activity-by-contact model, we create variant-to-gene maps to interpret the function of GWAS variants. Our work nominates a subset of variants to elucidate the molecular mechanisms involving GWAS-significant loci. It also highlights that in vitro human cellular models are a powerful platform for identifying and mechanistic studies of human trait-associated genetic variants in cell states that are inaccessible from other types of human samples.

Epigenetic and Transcriptional Regulation of Spontaneous and Sensory Activity Dependent Programs During Neuronal Circuit Development

Spontaneous activity generated before the onset of sensory transduction has a key role in wiring developing sensory circuits. From axonal targeting, to synapse formation and elimination, to the balanced integration of neurons into developing circuits, this type of activity is implicated in a variety of cellular processes. However, little is known about its molecular mechanisms of action, especially at the level of genome regulation. Conversely, sensory experience-dependent activity implements well-characterized transcriptional and epigenetic chromatin programs that underlie heterogeneous but specific genomic responses that shape both postnatal circuit development and neuroplasticity in the adult. In this review, we focus on our knowledge of the developmental processes regulated by spontaneous activity and the underlying transcriptional mechanisms. We also review novel findings on how chromatin regulates the specificity and developmental induction of the experience-dependent program, and speculate their relevance for our understanding of how spontaneous activity may act at the genomic level to instruct circuit assembly and prepare developing neurons for sensory-dependent connectivity refinement and processing.

Cancer proteogenomics: current impact and future prospects

Genomic analyses in cancer have been enormously impactful, leading to the identification of driver mutations and development of targeted therapies. But the functions of the vast majority of somatic mutations and copy number variants in tumours remain unknown, and the causes of resistance to targeted therapies and methods to overcome them are poorly defined. Recent improvements in mass spectrometry-based proteomics now enable direct examination of the consequences of genomic aberrations, providing deep and quantitative characterization of tumour tissues. Integration of proteins and their post-translational modifications with genomic, epigenomic and transcriptomic data constitutes the new field of proteogenomics, and is already leading to new biological and diagnostic knowledge with the potential to improve our understanding of malignant transformation and therapeutic outcomes. In this Review we describe recent developments in proteogenomics and key findings from the proteogenomic analysis of a wide range of cancers. Considerations relevant to the selection and use of samples for proteogenomics and the current technologies used to generate, analyse and integrate proteomic with genomic data are described. Applications of proteogenomics in translational studies and immuno-oncology are rapidly emerging, and the prospect for their full integration into therapeutic trials and clinical care seems bright.

Single-nucleus RNA sequencing identified cells with ependymal cell-like features enriched in neonatal mice after spinal cord injury

The adult mammalian central nervous system has limited regenerative ability, and spinal cord injury (SCI) often causes lifelong motor disability. While regeneration is limited in adults, injured spinal cord tissue can be regenerated and neural function can be almost completely restored in neonates. However, difference of cellular composition in lesion has not been well characterized. To gain insight into the age-dependent cellular reaction after SCI, we performed single-nucleus RNA sequencing, analyzing 4,076 nuclei from sham and injured spinal cords from adult and neonatal mice. Clustering analysis identified 18 cell populations. We identified previously undescribed cells with ependymal cell-like gene expression profile, the number of which was increased in neonates after SCI. Histological analysis revealed that these cells line the central canal under physiological conditions in both adults and neonates. We confirmed that they were enriched in the lesion only in neonates. We further showed that these cells were positive for the cellular markers of ependymal cells, astrocytes and radial glial cells. This study provides a deeper understanding of neonate-specific cellular responses after SCI, which may determine regenerative capacity.